Examples

This section provides comprehensive examples of using varunayan for various climate data analysis tasks.

Monsoon Analysis

Download and analyze monsoon precipitation patterns over India.

Python API

from varunayan import era5ify_geojson

# Download monsoon precipitation data
era5ify_geojson(
    request_id="india_monsoon_2020",
    variables=["total_precipitation", "2m_temperature"],
    start_date="2020-06-01",
    end_date="2020-09-30",
    json_file="india_states.geojson",
    dist_features=["state_name"],
    frequency="daily"
)

Command Line

varunayan geojson --request-id "india_monsoon_2020" \
  --variables "total_precipitation,2m_temperature" \
  --start "2020-06-01" --end "2020-09-30" \
  --geojson "india_states.geojson" \
  --dist-features "state_name" \
  --freq "daily"

Hurricane/Cyclone Analysis

Analyze atmospheric conditions during extreme weather events.

Pressure Level Winds

from varunayan import era5ify_bbox

# Download multi-level wind data during Cyclone Amphan
era5ify_bbox(
    request_id="amphan_cyclone",
    variables=["u_component_of_wind", "v_component_of_wind", "temperature"],
    start_date="2020-05-18",
    end_date="2020-05-21",
    north=25.0, south=15.0, east=95.0, west=85.0,
    dataset_type="pressure",
    pressure_levels=["1000", "925", "850", "700", "500"],
    frequency="hourly",
    resolution=0.1
)

Surface Conditions

# Surface pressure and wind patterns
varunayan bbox --request-id "amphan_surface" \
  --variables "mean_sea_level_pressure,10m_u_component_of_wind,10m_v_component_of_wind" \
  --start "2020-05-18" --end "2020-05-21" \
  --north 25.0 --south 15.0 --east 95.0 --west 85.0 \
  --freq "hourly" --res 0.1

Urban Heat Island Study

Compare temperatures between urban and rural areas.

City vs Surroundings

from varunayan import era5ify_point

# Urban center (Mumbai)
era5ify_point(
    request_id="mumbai_urban",
    variables=["2m_temperature", "surface_temperature"],
    start_date="2020-03-01",
    end_date="2020-05-31",
    latitude=19.0760,
    longitude=72.8777,
    frequency="hourly"
)

# Rural area nearby
era5ify_point(
    request_id="mumbai_rural",
    variables=["2m_temperature", "surface_temperature"],
    start_date="2020-03-01",
    end_date="2020-05-31",
    latitude=19.2,
    longitude=73.2,
    frequency="hourly"
)

Agricultural Applications

Climate data for crop monitoring and yield prediction.

Growing Season Analysis

from varunayan import era5ify_geojson

# Download data for agricultural regions
era5ify_geojson(
    request_id="punjab_agriculture",
    variables=[
        "2m_temperature", "total_precipitation",
        "2m_relative_humidity", "surface_solar_radiation_downwards"
    ],
    start_date="2020-04-01",  # Kharif season start
    end_date="2020-10-31",   # Kharif season end
    json_file="punjab_districts.geojson",
    dist_features=["district_name"],
    frequency="daily"
)

Frost Risk Assessment

# Daily minimum temperatures for winter wheat
varunayan geojson --request-id "wheat_frost_risk" \
  --variables "2m_temperature,2m_dewpoint_temperature" \
  --start "2019-12-01" --end "2020-03-31" \
  --geojson "wheat_growing_regions.geojson" \
  --dist-features "region_name" \
  --freq "daily"

Renewable Energy Assessment

Solar and wind resource evaluation.

Solar Resource Mapping

from varunayan import era5ify_bbox

# Solar radiation data for Rajasthan (major solar potential)
era5ify_bbox(
    request_id="rajasthan_solar",
    variables=[
        "surface_solar_radiation_downwards",
        "surface_net_solar_radiation",
        "total_cloud_cover"
    ],
    start_date="2019-01-01",
    end_date="2021-12-31",
    north=30.2, south=23.0, east=78.3, west=69.3,
    frequency="monthly"
)

Wind Energy Assessment

# Wind speeds at multiple heights for wind farm planning
varunayan bbox --request-id "gujarat_wind" \
  --variables "10m_u_component_of_wind,10m_v_component_of_wind,100m_u_component_of_wind,100m_v_component_of_wind" \
  --start "2020-01-01" --end "2020-12-31" \
  --north 24.7 --south 20.1 --east 74.5 --west 68.1 \
  --freq "daily"

Climate Change Studies

Long-term temperature and precipitation trends.

Extreme Events

# Heat wave analysis
varunayan bbox --request-id "delhi_heatwave_2019" \
  --variables "2m_temperature,maximum_2m_temperature_since_previous_post_processing" \
  --start "2019-05-01" --end "2019-06-30" \
  --north 29.0 --south 28.0 --east 77.5 --west 76.5 \
  --freq "daily"

Hydrology and Water Resources

Precipitation and evaporation analysis for water management.

Catchment Analysis

from varunayan import era5ify_geojson

# Water balance components for river basin
era5ify_geojson(
    request_id="ganga_basin_hydro",
    variables=[
        "total_precipitation", "total_evaporation",
        "runoff", "soil_temperature_level_1"
    ],
    start_date="2020-01-01",
    end_date="2020-12-31",
    json_file="ganga_basin.geojson",
    frequency="monthly"
)

Drought Monitoring

# Precipitation deficit analysis
varunayan geojson --request-id "maharashtra_drought_2019" \
  --variables "total_precipitation,soil_water_content,2m_temperature" \
  --start "2019-01-01" --end "2019-12-31" \
  --geojson "maharashtra_districts.geojson" \
  --dist-features "district_name" \
  --freq "monthly"

Aviation and Transport

Weather data for aviation route planning and safety.

Upper Air Analysis

from varunayan import era5ify_bbox

# Flight level weather conditions
era5ify_bbox(
    request_id="flight_route_weather",
    variables=[
        "temperature", "u_component_of_wind", "v_component_of_wind",
        "relative_humidity"
    ],
    start_date="2020-12-01",
    end_date="2020-12-31",
    north=35.0, south=8.0, east=95.0, west=65.0,  # India flight routes
    dataset_type="pressure",
    pressure_levels=["300", "250", "200"],  # Flight levels
    frequency="hourly"
)

Turbulence Analysis

# Wind shear and turbulence indicators
varunayan point --request-id "delhi_airport_winds" \
  --variables "u_component_of_wind,v_component_of_wind,temperature" \
  --start "2020-01-01" --end "2020-01-31" \
  --lat 28.5562 --lon 77.1000 \
  --dataset-type "pressure" \
  --pressure-levels "1000,925,850,700,500,300,250,200" \
  --freq "hourly"

High-Resolution Local Studies

Detailed analysis for small geographical areas.

Microclimate Analysis

from varunayan import era5ify_bbox

# High-resolution urban microclimate
era5ify_bbox(
    request_id="bangalore_microclimate",
    variables=[
        "2m_temperature", "10m_wind_speed", "2m_relative_humidity",
        "surface_solar_radiation_downwards"
    ],
    start_date="2020-06-01",
    end_date="2020-06-30",
    north=13.1, south=12.8, east=77.8, west=77.4,  # Bangalore city
    resolution=0.1,  # High resolution
    frequency="hourly"
)

Coastal Weather

# Coastal wind patterns for marine applications
varunayan bbox --request-id "mumbai_coastal" \
  --variables "10m_u_component_of_wind,10m_v_component_of_wind,mean_sea_level_pressure,significant_height_of_combined_wind_waves_and_swell" \
  --start "2020-06-01" --end "2020-09-30" \
  --north 19.3 --south 18.9 --east 72.9 --west 72.7 \
  --res 0.1 --freq "hourly"

Data Processing Tips

Handling Large Datasets

For large temporal or spatial extents, varunayan automatically chunks requests:

# This will be automatically chunked into smaller requests
era5ify_bbox(
    request_id="large_dataset",
    variables=["2m_temperature"],
    start_date="2000-01-01",  # 20+ years of data
    end_date="2020-12-31",
    north=50.0, south=0.0, east=100.0, west=50.0,
    frequency="daily"
)

Multiple Variables

Download different variable types in separate requests for efficiency:

# Surface variables
varunayan bbox --request-id "surface_vars" \
  --variables "2m_temperature,total_precipitation,10m_wind_speed" \
  --start "2020-01-01" --end "2020-12-31" \
  --north 30 --south 20 --east 80 --west 70

# Pressure level variables (separate request)
varunayan bbox --request-id "pressure_vars" \
  --variables "temperature,u_component_of_wind,v_component_of_wind" \
  --start "2020-01-01" --end "2020-12-31" \
  --north 30 --south 20 --east 80 --west 70 \
  --dataset-type "pressure" --pressure-levels "850,500,200"